Become a next-generation paving data science expert. Master the tools and techniques at the forefront of the paving data revolution.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
In the era of genomics, a revolution in medical discovery is emerging, and it is therefore important to better understand the genome and utilize the information from genomic data. Genomic data science is the field that applies statistics and data science to the genome.
This specialization covers the concepts and tools for understanding, analyzing, and interpreting data from next-generation sequencing experiments. It teaches the most common tools used in genomic data science, including:
This specialization is intended to serve as a standalone introduction to genomic data science or as a perfect complement to a bachelor’s or postdoctoral degree in biology, molecular biology, or genetics, for scientists in these fields who are interested in becoming familiar with data science tools and statistics.
To review courses in genomics data science for free, visit Coursera , click on the course, click enroll, and select the review option. Please note that you will not receive a certificate of completion if you choose this option.
Course 1
6 hours
4.6 (4,578 ratings)
This course introduces the basic biology of modern genomics and the experimental tools to measure it. We will introduce the central example in molecular biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You will also be introduced to key concepts in computing and data science.
Course 2
8 hours
4.3 (1,721 ratings)
This course provides an introduction to the Python programming language and the iPython notebook.
Course 3
12 hours
4.7 (894 ratings)
We will learn computational methods for analyzing DNA sequencing data. We will use Python to implement algorithms and analyze real genomes.
Course 4
11 hours
4.0 (553 ratings)
The course introduces the commands to manage and analyze folders, files, and large genomic datasets.
Course 5
8 hours
3.8 (371 ratings)
Learn how to use tools from the Bioconductor project to perform analysis of genomic data.
Course 6
9 hours
4.2 (362 ratings)
An introduction to the statistics behind the most popular genomic data science projects.
